EP2861766A2 - Biomarqueurs de méthylation pour le cancer du sein - Google Patents

Biomarqueurs de méthylation pour le cancer du sein

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Publication number
EP2861766A2
EP2861766A2 EP20130804083 EP13804083A EP2861766A2 EP 2861766 A2 EP2861766 A2 EP 2861766A2 EP 20130804083 EP20130804083 EP 20130804083 EP 13804083 A EP13804083 A EP 13804083A EP 2861766 A2 EP2861766 A2 EP 2861766A2
Authority
EP
European Patent Office
Prior art keywords
genes
methylation
hs3st2
rpia
tnfrsf8
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Application number
EP20130804083
Other languages
German (de)
English (en)
Other versions
EP2861766B1 (fr
EP2861766A4 (fr
Inventor
Hicham Mansour
Roberto INCITTI
Vladimir BAJIC
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
King Abdullah University of Science and Technology KAUST
Original Assignee
King Abdullah University of Science and Technology KAUST
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Publication of EP2861766A4 publication Critical patent/EP2861766A4/fr
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Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/154—Methylation markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/172—Haplotypes

Definitions

  • This invention relates to methylation biomarkers for breast cancer.
  • Breast cancer is the most frequent cancer among women both in developed and developing countries, with an estimated 1.38 million new cancer cases diagnosed in 2008 worldwide (23% of all cancers). Incidence rates vary from 19.3 per 100,000 women in Eastern Africa to 89.7 per 100,000 women in Western Europe. Rates are high (greater than 80 per 100,000) in all developed regions of the world except in Japan. However, rates are low (less than 40 per 100,000) in most of the developing regions. The range of mortality rates is much smaller (approximately 6-19 per 100,000) because of the more favorable survival rate in developed regions. As a result, breast cancer ranks as the fifth cause of death from cancer overall (458,000 deaths in 2008), but it is still the most frequent cause of cancer death in women in both developing (269,000 deaths, 12.7% of total) and developed regions (189,000) (1). In the United States, during 2011, the estimated new breast cancer cases are 229,060 and the estimated deaths amount to 39,920, for both sexes (breast cancer can also occur in men, although rarely) (2).
  • Testing the methylation status of a combination of several genes provides a highly sensitive and highly specific non-invasive tumor diagnosis for early stage breast cancer.
  • the low-cost tests can use easily obtained samples such as blood, serum, plasma, saliva, or urine.
  • a highly specific and highly selective method of detecting breast cancer in a patient includes obtaining a DNA sample from the patient; and measuring, from the DNA sample, a methylation level in a regulatory region of each of a plurality of genes selected from the group consisting of: FOXC1, ARFGEF1, CREBBP, MSH6, ARHGEF7, GNG4, RPIA, SLC2A14, BTG3, EDNRB, PRDM16, SST, HS3ST2, ITGA9, CDHl, Hoxa7, BMP6, CD40, and TNFRSF8.
  • the method can further include comparing the measured methylation level for each of the plurality of genes to a respective threshold methylation level, and, based on the comparisons, detecting the presence or absence of breast cancer in the patient with high sensitivity and high specificity.
  • the presence or absence of breast cancer can be detected with a sensitivity of greater than 95% and a specificity of greater than 95%, or with a sensitivity of greater than 99% and a specificity of greater than 99% based on the comparisons.
  • the plurality of genes can include nine or more of the genes listed.
  • the DNA sample can be obtained from a body fluid, wherein the body fluid is blood, serum, plasma, saliva, urine, stool, tissue, or a combination thereof.
  • the genes can be the genes of BC Set 1: ARFGEF1, ARHGEF7, CD40, CDH1, CREBBP, HS3ST2, RPIA, SST, and TNFRSF8.
  • the genes can be the genes of BC Set 2: ARFGEF1, ARHGE7, CD40, CDH1, HS3ST2, RPIA, SLC2A14, SST, and TNFRSF8.
  • the genes can be the genes of BC Set 3: ARFGEF1, ARHGE7, CDH1, CREBBP,
  • HS3ST2, RPIA, SLC2A14, SST, and TNFRSF8 are examples of RPIA, SLC2A14, SST, and TNFRSF8.
  • the genes can be the genes of BC Set 4: ARFGEF1, CD40, CDH1, CREBBP, HS3ST2, RPIA, SLC2A14, SST, and TNFRSF8.
  • the genes can be the genes of BC Set 5: ARFGEF1, CDH1, CREBBP, HS3ST2, PRDM16, RPIA, SLC2A14, SST, and TNFRSF8.
  • Screening tests for cancer, particularly breast cancer, based on currently known biomarkers have low sensitivity and low specificity, and few of such tests are evaluated on body fluids.
  • New combinations of biomarkers tested on readily and easily obtained body fluid samples can screen for breast cancer with high sensitivity and high specificity.
  • Sensitivity refers to the ability of a screening test to correctly identify true positives. For example, sensitivity can be expressed as a percentage, the proportion of actual positives which are correctly identified as such (e.g., the percentage of test subjects having cancer correctly identified by the test as having cancer). A test with high sensitivity has a low rate of false negatives.
  • Specificity refers to the ability of a screening test to correctly identify true negatives. For example, specificity can be expressed as a percentage, the proportion of actual negatives which are correctly identified as such (e.g., the percentage of test subjects not having cancer correctly identified by the test as not having cancer). A test with high specificity has a low rate of false positives.
  • Using a test based on a combination of biomarkers provides a screening test for breast cancer that can have higher sensitivity, higher specificity, or both higher sensitivity and higher specificity, than tests based on a single biomarker.
  • a screening test has high levels of both sensitivity and specificity.
  • Alterations of DNA methylation patterns have been recognized as a common change in human cancers. Aberrant methylation of normally unmethylated CpG islands in or near the promoter region of many genes has been associated with transcriptional inactivation of important genes, including tumor suppressor genes, DNA repair genes, and metastasis inhibitor genes. Therefore, detection of aberrant promoter methylation of cancer-related genes can be an efficient method for the diagnosis, prognosis and/or detection of tumors.
  • a challenge in identifying DNA methylation patterns is that 5-methylcytosine is indistinguishable from cytosine in its hybridization behavior.
  • the specific reaction of bisulfite with cytosine is therefore useful in investigating DNA methylation.
  • Bisulfite can convert cytosine, but not 5-methylcytosine, to uracil.
  • Uracil corresponds in its base-pairing behavior to thymidine, and thus allows 5-methylcytosine to be differentiated from cytosine using "standard" molecular biological techniques, for example, by amplification and hybridization or sequencing.
  • methylation-specific arbitrarily primed PCR methylated CpG island amplification (MCA), differential methylation hybridization (DMH), and restriction landmark genomic scanning (RLGS)
  • MCA methylated CpG island amplification
  • DH differential methylation hybridization
  • RLGS restriction landmark genomic scanning
  • MSP methylation specific-PCR
  • Methods Methods for determining the length of a sample DNA.
  • a gel based MSP assay one set of primers amplifies the unmethylated version and one set amplifies the methylated version, and the presence of a band on a gel in each reaction determines the methylation state.
  • amplification with methylation specific primers with or without probes is normalized to the total amount of input DNA to determine the fraction of DNA methylated for each region of interest.
  • Alternative marker analysis methods include oligonucleotide arrays, primer extension, and sequencing.
  • Biomarkers for cancer were identified in the following way. Public gene expression data for normal and cancer cells was mined to identify genes showing reduced expression levels in cancer cells compared to normal cells. Those genes having reduced expression levels in cancer and CpG promoter islands were further investigated. It is generally known that reduced expression levels for genes with CpG islands is correlated with methylation of the CpG islands. For each of the genes selected for further investigation, a quantitative correlation between expression level and extent of methylation was established. Then, based on that quantitative correlation, a threshold methylation level was established for each gene. The threshold level was set as the highest extent of methylation seen in the normal samples, plus an additional amount, e.g., 5%, 10%, 25%, 33%, etc.
  • the biomarkers can be used in the following way.
  • a DNA sample is obtained from a subject.
  • the DNA sample can derived from any suitable source, including but not limited to blood, serum, plasma, saliva, urine, stool, tissue, or a combination of these.
  • the DNA sample is derived from a source other than tissue; e.g., blood, serum, plasma, saliva, or urine.
  • the methylation status of several the biomarker genes identified in the manner described above is then tested by any suitable method for determining the extent of DNA methylation, including but not limited to methylation specific PCR; methylated CpG island amplification; differential methylation hybridization; or restriction landmark genomic scanning.
  • the assessment of methylation is a very stable procedure since, unlike, .e.g., measuring mRNA levels, it is much less influenced by experimental parameters.
  • the experimentally determined methylation levels for each gene are first compared to their respective threshold levels, and scored as true or false.
  • the result of the test is both highly sensitive and highly specific.
  • the test can have a sensitivity of no less than 90%, no less than 95%, no less than 96%, no less than 97%, no less than 98%, no less than 99%, or 100%.
  • the test can have a specificity of no less than 90%, no less than 95%, no less than 96%, no less than 97%, no less than 98%, no less than 99%, or 100%. In some instances, both sensitivity and specificity can be no less than 90%, no less than 95%, no less than 96%, no less than 97%, no less than 98%, no less than 99%, or 100%.
  • biomarkers already published and/or patented have low sensitivity and low specificity and few of them are evaluated on body fluid.
  • the present combinations of the biomarkers proposed in this invention are unique for the diagnosis of BC patients.
  • biomarkers methylated promoter regions of a set of genes— for breast cancer were identified and then validated in different combinations.
  • the genes were known and some have been previously identified as biomarkers for cancers, but the set, and the combinations of genes from within the set, are new.
  • the base set of genes identified is as follows:
  • Base BC Set FOXC1, ARFGEF1, CREBBP, MSH6, ARHGEF7, GNG4, RPIA, SLC2A14, BTG3, EDNRB, PRDM16, SST, HS3ST2, ITGA9, CDHl, Hoxa7, BMP6, CD40, and TNFRSF8.
  • test based methylation status of all nineteen of these genes provides 97% sensitivity and 100% specificity for breast cancer based on our data (see above).
  • Tests based on smaller sets (e.g., sets of nine or more) of these genes can also provide 97% sensitivity and 100% specificity for breast cancer. Those smaller sets include:
  • BC Set 1 ARFGEF1, ARHGEF7, CD40, CDHl, CREBBP, HS3ST2, RPIA, SST, and TNFRSF8.
  • BC Set 3 ARFGEF1, ARHGE7, CDHl, CREBBP, HS3ST2, RPIA, SLC2A14, SST, and TNFRSF8.
  • BC Set 4 ARFGEF1, CD40, CDHl, CREBBP, HS3ST2, RPIA, SLC2A14, SST, and TNFRSF8.
  • BC Set 5 ARFGEF1, CDHl, CREBBP, HS3ST2, PRDM16, RPIA, SLC2A14, SST, and TNFRSF8.
  • 19 genes show a as potential screening markers for breast cancer at high level of sensitivity and specificity even over 5% of threshold (highest methylation value in normal patients + an error margin of 0.05.
  • the error margin is defined as 0.05 times the difference between the full methylation value (100% methylation) and the highest methylation value in controls).
  • the 19 genes described in what follows are predicted hypermethylated in BC versus normal, rank among the best p-values using Wilcoxon signed- rank test or among the most discriminating ones based on the threshold, and keep their ability to discriminate under stringent conditions: FOXCl (Gene ID: 2296), ARFGEF1 (Gene ID: 10565), CREBBP (Gene ID: 1387), MSH6 (Gene ID: 2956), ARHGEF7 (Gene ID: 8874), GNG4 (Gene ID: 2786), RPIA (Gene ID: 22934), SLC2A14 (Gene ID: 144195), BTG3 (Gene ID: 10950), EDNRB (Gene ID: 1910), PRDM16 (Gene ID: 63976), SST (Gene ID: 6750), HS3ST2 (Gene ID: 9956), ITGA9 (Gene ID: 3680), CDHl (Gene ID: 999), Hoxa7 (Gene ID: 3
  • Table 1 shows predicted methylation values from the 32 breast cancer patients.

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  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Organic Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Engineering & Computer Science (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Zoology (AREA)
  • Genetics & Genomics (AREA)
  • Wood Science & Technology (AREA)
  • Physics & Mathematics (AREA)
  • Biotechnology (AREA)
  • Microbiology (AREA)
  • Molecular Biology (AREA)
  • Hospice & Palliative Care (AREA)
  • Biophysics (AREA)
  • Oncology (AREA)
  • Biochemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Abstract

La présente invention porte sur différentes combinaisons de biomarqueurs basés sur l'état de méthylation qui peuvent être utilisés pour le test et la recherche du cancer de la sein e avec une grande sensibilité et une grande spécificité.
EP13804083.7A 2012-06-13 2013-06-11 Biomarqueurs de méthylation pour le cancer du sein Active EP2861766B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201261659239P 2012-06-13 2012-06-13
PCT/IB2013/002012 WO2013186639A2 (fr) 2012-06-13 2013-06-11 Biomarqueurs de méthylation pour le cancer du sein

Publications (3)

Publication Number Publication Date
EP2861766A2 true EP2861766A2 (fr) 2015-04-22
EP2861766A4 EP2861766A4 (fr) 2016-03-02
EP2861766B1 EP2861766B1 (fr) 2018-08-08

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EP13804083.7A Active EP2861766B1 (fr) 2012-06-13 2013-06-11 Biomarqueurs de méthylation pour le cancer du sein

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US (4) US9982307B2 (fr)
EP (1) EP2861766B1 (fr)
AU (1) AU2013276226A1 (fr)
CA (1) CA2876393A1 (fr)
WO (1) WO2013186639A2 (fr)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA2308564A1 (fr) * 2000-05-15 2001-11-15 Mark J. Frazer Structure de communication pour liaisons multiplexees
US9982307B2 (en) 2012-06-13 2018-05-29 King Abdullah University Of Science And Technology Methylation biomarkers for breast cancer
US10613090B2 (en) 2014-05-09 2020-04-07 Ascendant Diagnostics, LLC Methods of detecting cancer
WO2017053915A1 (fr) * 2015-09-24 2017-03-30 Caris Science, Inc. Procédé, appareil et produit programme d'ordinateur permettant d'analyser des données biologiques
KR101910168B1 (ko) 2016-07-05 2018-10-19 이화여자대학교 산학협력단 암세포 검출용 인산화 Cdh1 펩타이드 바이오마커
EP3775289A1 (fr) * 2018-03-26 2021-02-17 King Abdullah University Of Science And Technology Biomarqueurs à base de méthylation pour le dépistage, le diagnostic ou le pronostic du cancer du sein
WO2020069350A1 (fr) 2018-09-27 2020-04-02 Grail, Inc. Marqueurs de méthylation et panels de sondes de méthylation ciblées
CN114075605A (zh) * 2022-01-19 2022-02-22 博尔诚（北京）科技有限公司 基于甲基化增强基因表达（mege）的癌症标志物筛选方法

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JP2008506407A (ja) 2004-07-18 2008-03-06 エピゲノミクス アーゲー 乳房細胞増殖性疾患を検出するためのエピジェネティックな方法および核酸
US8268549B2 (en) 2005-04-15 2012-09-18 University Of Maryland, Baltimore Method and assay for determining methylation of GAL3 promoter for early diagnosis of prostate cancer
WO2006128140A2 (fr) 2005-05-27 2006-11-30 Dana-Farber Cancer Institute, Inc. Methylation et expression de genes
US20070141582A1 (en) 2005-12-15 2007-06-21 Weiwei Li Method and kit for detection of early cancer or pre-cancer using blood and body fluids
WO2009108917A2 (fr) * 2008-02-29 2009-09-03 Oncomethylome Sciences, S.A. Marqueurs pour la détection améliorée du cancer du sein
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US20100303795A1 (en) * 2009-05-27 2010-12-02 Soerensen Karina Dalsgaard Marker of prostate cancer
EP2486149B1 (fr) 2009-08-06 2015-06-17 John Wayne Cancer Institute Diagnostic du cancer du sein primitif et de type basal métastatique et d'autres types de cancer
WO2012138609A2 (fr) * 2011-04-04 2012-10-11 The Board Of Trustees Of The Leland Stanford Junior University Biomarqueurs de méthylation pour le diagnostic du cancer de la prostate
WO2013124740A2 (fr) 2012-02-23 2013-08-29 Stichting Vu-Vumc Dysfonctionnement de la protéine brca et signatures arnm utiles dans l'identification de patients atteints de tumeurs dues au dysfonctionnement de la protéine brca et prévision des bénéfices d'une thérapie anti-cancer sur des patients atteints de cancer
US9982307B2 (en) * 2012-06-13 2018-05-29 King Abdullah University Of Science And Technology Methylation biomarkers for breast cancer

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Publication number Publication date
AU2013276226A1 (en) 2015-02-05
CA2876393A1 (fr) 2013-12-19
WO2013186639A2 (fr) 2013-12-19
WO2013186639A3 (fr) 2014-05-30
EP2861766B1 (fr) 2018-08-08
US20150141262A1 (en) 2015-05-21
US20150292025A1 (en) 2015-10-15
EP2861766A4 (fr) 2016-03-02
US9976187B2 (en) 2018-05-22
WO2013186639A8 (fr) 2015-01-29
US20180237867A1 (en) 2018-08-23
US9982307B2 (en) 2018-05-29
US20180327861A1 (en) 2018-11-15

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